Sample-size determination for decentralized clinical trials.

Abstract

Background: Decentralized clinical trials (DCTs) are increasingly recognized and utilized in epidemiology studies and drug development. A critical step in designing DCTs is determining the sample size-a topic that is insufficiently covered in the literature. This paper aims to propose a sample-size-calculation method for designing DCTs.

Methods: A key challenge in analysing DCTs is that data collected onsite and offsite may differ in both variance and mean. The proposed approach employs the weighted z-test to account for such heterogeneity and combines test statistics based on onsite and offsite data. Closed-form sample-size formulas are derived for both cross-sectional studies with independent data and longitudinal or cluster studies with correlated data. The validity of the method is demonstrated by using two examples: cardiovascular disease and pain-management trials.

Results: Our theoretical derivations and numerical studies show that the proposed method enables accurate and robust sample-size determination for DCTs across varying effect sizes, intraclass correlation coefficients for correlated data, variances of onsite and offsite measurements, and ratios of onsite and offsite patients. Compared with the conventional sample-size formula developed for traditional trials involving onsite patients only, the proposed method offers more precise sample-size determination and better preservation of the study power.

Conclusion: The proposed method offers an accurate and easy-to-use tool, supported by user-friendly software, for determining sample sizes for DCTs, encompassing both cross-sectional and longitudinal or cluster trials.